Distinct cellular microRNA expression patterns during influenza virus BJ501 and PR8 infections.

<p>The columns correspond to expression patterns of differentially expressed microRNAs during the influenza virus BJ501 and PR8 infections relative to mock-infected samples on 2 dpi and 5 dpi. Significance was determined using a fold-change threshold of at least 2 and a <i>P</i> value cutoff of 0.05. The red color represents up-regulation, while the green color indicates down-regulation.</p

MicroRNA Expression Profile of Mouse Lung Infected with 2009 Pandemic H1N1 Influenza Virus

<div><p>MicroRNAs have been implicated in the regulation of gene expression of various biological processes in a post-transcriptional manner under physiological and pathological conditions including host responses to viral infections. The 2009 pandemic H1N1 influenza virus is an emerging reassortant strain of swine, human and bird influenza virus that can cause mild to severe illness and even death. To further understand the molecular pathogenesis of the 2009 pandemic H1N1 influenza virus, we profiled cellular microRNAs of lungs from BALB/c mice infected with wild-type 2009 pandemic influenza virus A/Beijing/501/2009 (H1N1) (hereafter referred to as BJ501) and mouse-adapted influenza virus A/Puerto Rico/8/1934 (H1N1) (hereafter referred to as PR8) for comparison. Microarray analysis showed both the influenza virus BJ501 and PR8 infection induced strain- and temporal-specific microRNA expression patterns and that their infection caused a group of common and distinct differentially expressed microRNAs. Characteristically, more differentially expressed microRNAs were aroused on day 5 post infection than on day 2 and more up-regulated differentially expressed microRNAs were provoked than the down-regulated for both strains of influenza virus. Finally, 47 differentially expressed microRNAs were obtained for the infection of both strains of H1N1 influenza virus with 29 for influenza virus BJ501 and 43 for PR8. Among them, 15 microRNAs had no reported function, while 32 including miR-155 and miR-233 are known to play important roles in cancer, immunity and antiviral activity. Pathway enrichment analyses of the predicted targets revealed that the transforming growth factor-β (TGF-β) signaling pathway was the key cellular pathway associated with the differentially expressed miRNAs during influenza virus PR8 or BJ501 infection. To our knowledge, this is the first report of microRNA expression profiles of the 2009 pandemic H1N1 influenza virus in a mouse model, and our findings might offer novel therapy targets for influenza virus infection. </p> </div

The number of differentially expressed microRNAs during influenza virus BJ501 and PR8 infections.

<p>The y axis indicates the number of differentially expressed microRNAs. Significance was determined using a fold-change threshold of at least 2 and a nominal <i>P</i> value cutoff of 0.05.</p

Top 10 significantly enriched GO terms of molecular function for the predicted targets.

<p>(A) Top ten significantly enriched GO terms of molecular function for the predicted targets of differentially expressed microRNAs in response to influenza virus BJ501 infection. (B) Top 10 significantly enriched GO terms of molecular function for the predicted targets of differentially expressed microRNAs in response to influenza virus PR8 infection.</p

KEGG pathway analysis of the predicted targets of differentially expressed microRNAs.

<p>(A) The top three significantly enriched pathways in influenza virus BJ501 infection. (B) The top three significantly enriched pathways in influenza virus PR8 infection.</p

The microRNA expression patterns in response to influenza virus BJ501 and PR8 infections.

<p>The expression patterns of 230 detected microRNAs of influenza virus BJ501 and PR8 infections to the mock-infected controls on 2 dpi and 5 dpi were depicted with a clustered heatmap. The clustering tree is shown on the top and left sides. The red color represents up-regulation, while the green color indicates down-regulation.</p

Comparison of differentially expressed microRNAs between the influenza virus BJ501 and PR8 infections.

<p>(A) Venn diagram of differentially expressed microRNAs during influenza virus BJ501 and PR8 infections relative to the mock-infected control on 2 dpi. (B) Venn diagram of differentially expressed microRNAs during influenza virus BJ501 and PR8 infections relative to the mock-infected control on 5 dpi. The diagram displays the names of differentially expressed microRNAs. The red color represents up-regulated microRNAs, while the green color indicates down-regulated microRNAs.</p

Real-time reverse transcription polymerase chain reaction (RT-PCR) verification of microRNA microarray.

<p>Nine differentially expressed microRNAs were selected from microarray datasets and examined by real-time RT-PCR. The fold change of a particular microRNA in the influenza virus BJ501 or PR8 infection relative to the mock infection was calculated. The fold-change from the real-time RT-PCR was determined using the 2-^△△Ct method and all microRNA expression values were normalized against the U6 endogenous control. Data from real-time RT-PCR are shown as mean ± standard deviation (SD).</p

Higher Isolation of NDM<i>-</i>1 Producing <i>Acinetobacter baumannii</i> from the Sewage of the Hospitals in Beijing

<div><p>Multidrug resistant microbes present in the environment are a potential public health risk. In this study, we investigate the presence of New Delhi metallo-β-lactamase 1 (NDM-1) producing bacteria in the 99 water samples in Beijing City, including river water, treated drinking water, raw water samples from the pools and sewage from 4 comprehensive hospitals. For the <i>bla</i>_NDM-1 positive isolate, antimicrobial susceptibility testing was further analyzed, and Pulsed Field Gel Electrophoresis (PFGE) was performed to determine the genetic relationship among the NDM-1 producing isolates from sewage and human, as well as the clinical strains without NDM-1. The results indicate that there was a higher isolation of NDM-1 producing <i>Acinetobacter baumannii</i> from the sewage of the hospitals, while no NDM-1 producing isolates were recovered from samples obtained from the river, drinking, or fishpond water. Surprisingly, these isolates were markedly different from the clinical isolates in drug resistance and pulsed field gel electrophoresis profiles, suggesting different evolutionary relationships. Our results showed that the hospital sewage may be one of the diffusion reservoirs of NDM-1 producing bacteria.</p></div